kplug / demo_ner.py
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# coding=utf-8
# author: xusong <xusong28@jd.com>
# time: 2022/8/25 16:57
"""
## ner demo
- https://gradio.app/named_entity_recognition/
- https://huggingface.co/dslim/bert-base-NER?text=My+name+is+Wolfgang+and+I+live+in+Berlin
"""
from transformers import pipeline
import gradio as gr
ner_pipeline = pipeline("ner")
examples = [
"Does Chicago have any stores and does Joe live here?",
]
import json
def ner(text):
output = ner_pipeline(text)
for ent in output:
ent["score"] = float(ent["score"])
aa = {"text": text, "entities": output}
return aa, output
demo = gr.Interface(
ner,
inputs=gr.Textbox(placeholder="Enter sentence here..."),
outputs=
[
gr.HighlightedText(
label="NER",
show_legend=True,
),
gr.JSON(),
],
examples=examples)
demo.launch()